Genomics and proteomics approaches to the study of cancer-stroma interactions

Background

The development and progression of cancer depend on its genetic characteristics as well as on the interactions with its microenvironment. Understanding these interactions may contribute to diagnostic and prognostic evaluations and to the development of new cancer therapies. Aiming to investigate potential mechanisms by which the tumor microenvironment might contribute to a cancer phenotype, we evaluated soluble paracrine factors produced by stromal and neoplastic cells which may influence proliferation and gene and protein expression.

Methods

The study was carried out on the epithelial cancer cell line (Hep-2) and fibroblasts isolated from a primary oral cancer. We combined a conditioned-medium technique with subtraction hybridization approach, quantitative PCR and proteomics, in order to evaluate gene and protein expression influenced by soluble paracrine factors produced by stromal and neoplastic cells.

Results

We observed that conditioned medium from fibroblast cultures (FCM) inhibited proliferation and induced apoptosis in Hep-2 cells. In neoplastic cells, 41 genes and 5 proteins exhibited changes in expression levels in response to FCM and, in fibroblasts, 17 genes and 2 proteins showed down-regulation in response to conditioned medium from Hep-2 cells (HCM). Nine genes were selected and the expression results of 6 down-regulated genes (ARID4A, CALR, GNB2L1, RNF10, SQSTM1, USP9X) were validated by real time PCR.

Conclusions

A significant and common denominator in the results was the potential induction of signaling changes associated with immune or inflammatory response in the absence of a specific protein.

     

Study of the tumor microenvironment during breast cancer progression

Background

Different cells and mediators in the tumor microenvironment play important roles in the progression of breast cancer. The aim of this study was to determine the composition of the microenvironment during tumor progression in order to discover new related biomarkers and potentials for targeted therapy.

Methods

In this study, breast cancer biopsies from four different stages, and control breast biopsies were collected. Then, the mRNA expression of several markers related to different CD4⁺ T cell subsets including regulatory T cells (Treg), T helper (Th) type 1, 2 and 17 were determined. In addition, we investigated the expression of two inflammatory cytokines (TNF-α and IL-6) and inflammatory mediators including FASL, IDO, SOCS1, VEGF, and CCR7.

Results

The results showed that the expression of Th1 and Th17 genes was decreased in tumor tissues compared to control tissues. In addition, we found that the gene expression related to these two cell subsets decreased during cancer progression. Moreover, the expression level of TNF-α increased with tumor progression.

Conclusion

We conclude that the expression of genes related to immune response and inflammation is different between tumor tissues and control tissues. In addition, this difference was perpetuated through the different stages of cancer.

     

Treatment with Imiquimod enhances antitumor immunity induced by therapeutic HPV DNA vaccination

Background

There is an urgent need to develop new innovative therapies for the control of advanced cancer. The combination of antigen-specific immunotherapy with the employment of immunomodulatory agents has emerged as a potentially plausible approach for the control of advanced cancer.

Methods

In the current study, we explored the combination of the DNA vaccine encoding calreticulin (CRT) linked to human papillomavirus type 16 (HPV-16) E7 antigen (CRT/E7) with the TLR7 agonist imiquimod for their ability to generate E7-specific immune responses and antitumor effects in tumor-bearing mice.

Results

We observed that treatment with CRT/E7 DNA in combination with imiquimod leads to an enhancement in the E7-specific CD8+ T cell immune responses and a decrease in the number of myeloid-derived suppressor cells in the tumor microenvironment of tumor-bearing mice. Furthermore, treatment with CRT/E7 DNA in combination with imiquimod leads to significantly improved antitumor effects and prolonged survival in treated mice. In addition, treatment with imiquimod led to increased number of NK1.1+ cells and F4/80+ cells in the tumor microenvironment. Macrophages and NK1.1+ cells were found to play an important role in the antitumor effects mediated by treatment with CRT/E7 DNA in combination with imiquimod.

Conclusions

Thus, our data suggests that the combination of therapeutic HPV DNA vaccination with topical treatment with the TLR7 agonist imiquimod enhances the antitumor immunity induced by DNA vaccination. The current study has significant implications for future clinical translation.

     

PTEN at the interface of immune tolerance and tumor suppression

Background

PTEN is well known to function as a tumor suppressor that antagonizes oncogenic signaling and maintains genomic stability. The PTEN gene is frequently deleted or mutated in human cancers and the wide cancer spectrum associated with PTEN deficiency has been recapitulated in a variety of mouse models of Pten deletion or mutation. Pten mutations are highly penetrant in causing various types of spontaneous tumors that often exhibit resistance to anticancer therapies including immunotherapy. Recent studies demonstrate that PTEN also regulates immune functionality.

Objective

To understand the multifaceted functions of PTEN as both a tumor suppressor and an immune regulator.

Methods

This review will summarize the emerging knowledge of PTEN function in cancer immunoediting. In addition, the mechanisms underlying functional integration of various PTEN pathways in regulating cancer evolution and tumor immunity will be highlighted.

Results

Recent preclinical and clinical studies revealed the essential role of PTEN in maintaining immune homeostasis, which significantly expands the repertoire of PTEN functions. Mechanistically, aberrant PTEN signaling alters the interplay between the immune system and tumors, leading to immunosuppression and tumor escape.

Conclusion

Rational design of personalized anti-cancer treatment requires mechanistic understanding of diverse PTEN signaling pathways in modulation of the crosstalk between tumor and immune cells.

     

Control of spontaneous ovarian tumors by CD8+ T cells through NKG2D-targeted delivery of antigenic peptide

Background

There is an urgent need to develop targeted therapies for the control of advanced stage ovarian cancer because it is the most deadly gynecologic cancer. Antigen-specific immunotherapy is a promising approach because of the potential of the immune system to specifically target tumors without the toxicity associated with traditional chemoradiation. However, one of the major limitations for antigen-specific cancer immunotherapy is the pre-existing immune tolerance against endogenous targeted tumor antigens that frequently evolves during carcinogenesis. Here, we described the creation of a therapeutic agent comprised of a tumor-homing module fused to a functional domain capable of selectively rendering tumor cells sensitive to foreign antigen-specific CD8+ T cell-mediated immune attack, thereby circumventing many aspects of immune tolerance. The tumor-homing module, NKG2D, specifically binds to NKG2D ligand that is commonly overexpressed in ovarian tumors. The functional domain is comprised of the Fc portion of IgG2a protein and foreign immunogenic CD8⁺ T cell epitope flanked by furin cleavage sites (R), which can be recognized and cleaved by furin that is highly expressed in the tumor microenvironment.

Results

We show that this therapeutic chimeric protein specifically loaded antigenic epitope onto the surface of NKG2D ligand-expressing ovarian tumor cells, rendering ovarian tumors susceptible to antigen-specific CTL-mediated killing in vitro. Furthermore, we show that intraperitoneal administration of our therapeutic chimeric protein followed by adoptive transfer of antigen-specific CD8+ T cells generates potent antitumor effects and significant accumulation of antigen-specific CD8+ T cells in the tumor loci.

Conclusions

Our findings have promise for bypassing immune tolerance to enhance cancer immunotherapy.

     

Metastatic tumor cells – genotypes and phenotypes

Background

Metastasis is the primary cause of mortality in cancer patients. Therefore, elucidating the genetics and epigenetics of metastatic tumor cells and the mechanisms by which tumor cells acquire metastatic properties constitute significant challenges in cancer research.

Objective

To summarize the current understandings of the specific genotype and phenotype of the metastatic tumor cells.

Method and Result

In-depth genetic analysis of tumor cells, especially with advances in the next-generation sequencing, have revealed insights of the genotypes of metastatic tumor cells. Also, studies have shown that the cancer stem cell (CSC) and epithelial to mesenchymal transition (EMT) phenotypes are associated with the metastatic cascade.

Conclusion

In this review, we will discuss recent advances in the field by focusing on the genomic instability and phenotypic dynamics of metastatic tumor cells.

     

Analysis of PD-1 related immune transcriptional profile in different cancer types

Background

Programmed cell death 1 (PD-1) functions as an immune checkpoint in the process of anti-tumor immune response. The PD-1 blockade is now becoming a fundamental part in cancer immunotherapy. So it’s essential to elicit the PD-1 related immune process in different types of cancer.

Methods

The Cancer Genome Atlas was used to collect the RNA-seq data of 33 cancer types. The microenvironment cell populations-counter was used to analyze the immune cell infiltrates. KEGG and GO analysis were performed to investigate PD-1 associated biological process. Kaplan–Meier survival curves and Cox’s proportional hazards model were performed for prognostic value analysis.

Results

We demonstrated that PD-1 expression varied in different cancer types. The uveal melanoma had a low PD-1 expression and poor infiltrated with immune cells. But it showed the strong correlation of PD-1 with the most types of immune cells. The PD-1 demonstrated a robust relationship with other immunomodulators and showed its involvement in critical functions correlated with anti-tumor immune pathways. Survival analysis indicated the PD-1 expression suggested different prognosis in different cancer types.

Conclusions

Our investigations promote a better understanding of the PD-1 blockade and provide PD-1 related personized combined immunotherapy for different types of cancer patients.

     

Tryptophan metabolism along the kynurenine and serotonin pathways reveals substantial differences in colon and rectal cancer

Introduction

Induction of tryptophan (TRP) catabolism is an adaptation mechanism to restrict excessive acute immune response in tissues. In the tumour microenvironment, TRP catabolism’s dysregulation plays an important role in local antitumour immune response suppression.

Aim

We investigated changes in the plasma concentrations of TRP and its metabolites in a cohort of colorectal cancer (CRC) patients at different tumour stages and in subjects at risk of developing CRC. TRP metabolites were assessed along kynurenine and serotonin pathways, and the activity of involved enzymes and their tissue expression were monitored.

Method

Plasmatic levels of tryptophan metabolites were quantified in 80 patients’ plasma samples by means of High-Pressure Liquid Chromatography coupled to UltraViolet/Fluorescence Detectors (HPLC-UV/FD), after a simple dilution step. Tissue IDO1 gene expression during to the adenoma-carcinoma sequence and samples were obtained from formalin-fixed and paraffin-embedded (FFPE) normal colon and tumour tissues from a subset of patients (n?=?21).

Results

Altered TRP concentrations were detected in plasma samples concomitant to pre-cancerous lesion and persisted during the adenoma-carcinoma transition. Moreover, the anatomical site of cancer lesions (colon or rectum) strongly influences the TRP metabolic profiles. Colon cancer patients exhibited increased TRP catabolism with respect to those affected by rectal cancer, suggesting that TRP’s metabolism alterations play an important role in the onset and progression of colon cancer, but not in those of rectal cancer.

     

Proteomic profiling identifies markers for inflammation-related tumor–fibroblast interaction

Background

Cancer associated fibroblasts are activated in the tumor microenvironment and contribute to tumor progression, angiogenesis, extracellular matrix remodeling, and inflammation.

Methods

To identify proteins characteristic for fibroblasts in colorectal cancer we used liquid chromatography-tandem mass spectrometry to derive protein abundance from whole-tissue homogenates of human colorectal cancer/normal mucosa pairs. Alterations of protein levels were determined by two-sided t test with greater than threefold difference and an FDR of < 0.05. Public available datasets were used to predict proteins of stromal origin and link protein with mRNA regulation. Immunohistochemistry confirmed the localization of selected proteins.

Results

We identified a set of 24 proteins associated with inflammation, matrix organization, TGFβ receptor signaling and angiogenesis mainly originating from the stroma. Most prominent were increased abundance of SerpinB5 in the parenchyme and latent transforming growth factor β-binding protein, thrombospondin-B2, and secreted protein acidic-and-cysteine-rich in the stroma. Extracellular matrix remodeling involved collagens type VIII, XII, XIV, and VI as well as lysyl-oxidase-2. In silico analysis of mRNA levels demonstrated altered expression in the tumor and the adjacent normal tissue as compared to mucosa of healthy individuals indicating that inflammatory activation affected the surrounding tissue. Immunohistochemistry of 26 tumor specimen confirmed upregulation of SerpinB5, thrombospondin B2 and secreted protein acidic-and-cysteine-rich.

Conclusions

This study demonstrates the feasibility of detecting tumor- and compartment-specific protein-signatures that are functionally meaningful by proteomic profiling of whole-tissue extracts together with mining of RNA expression datasets. The results provide the basis for further exploration of inflammation-related stromal markers in larger patient cohorts and experimental models.

     

Are online prediction tools a valid alternative to genomic profiling in the context of systemic treatment of ER-positive breast cancer?

Background

Clinicians use clinical and pathological parameters, such as tumour size, grade and nodal status, to make decisions on adjuvant treatments for breast cancer. However, therapeutic decisions based on these features tend to vary due to their subjectivity. Computational and mathematical algorithms were developed using clinical outcome data from breast cancer registries, such as Adjuvant! Online and NHS PREDICT. More recently, assessments of molecular profiles have been applied in the development of better prognostic tools.

Methods

Based on the available literature on online registry-based tools and genomic assays, we evaluated whether these online tools could be valid and accurate alternatives to genomic and molecular profiling of the individual breast tumour in aiding therapeutic decisions, particularly in patients with early ER-positive breast cancer.

Results and conclusions

Early breast cancer is currently considered a systemic disease and a complex ecosystem with behaviour determined by the complex genetic and molecular signatures of the tumour cells, mammary stem cells, microenvironment and host immune system. We anticipate that molecular profiling will continue to evolve, expanding beyond the primary tumour to include the tumour microenvironment, cancer stem cells and host immune system. This should further refine therapeutic decisions and optimise clinical outcome.This article was specially invited by the editors and represents work by leading researchers.

     

Quantitative phosphoproteomic analysis reveals reciprocal activation of receptor tyrosine kinases between cancer epithelial cells and stromal fibroblasts

Background

Cancer-associated fibroblasts (CAFs) are one of the most important components of tumor stroma and play a key role in modulating tumor growth. However, a mechanistic understanding of how CAFs communicate with tumor cells to promote their proliferation and invasion is far from complete. A major reason for this is that most current techniques and model systems do not capture the complexity of signal transduction that occurs between CAFs and tumor cells.

Methods

In this study, we employed a stable isotope labeling with amino acids in cell culture (SILAC) strategy to label invasive breast cancer cells, MDA-MB-231, and breast cancer patient-derived CAF cells. We used an antibody-based phosphotyrosine peptide enrichment method coupled to LC–MS/MS to catalog and quantify tyrosine phosphorylation-mediated signal transduction events induced by the bidirectional communication between patient-derived CAFs and tumor cells.

Results

We discovered that distinct signaling events were activated in CAFs and in tumor epithelial cells during the crosstalk between these two cell types. We identified reciprocal activation of a number of receptor tyrosine kinases including EGFR, FGFR1 and EPHA2 induced by this bidirectional communication.

Conclusions

Our study not only provides insights into the mechanisms of the interaction between CAFs and tumor cells, but the model system described here could be used as a prototype for analysis of intercellular communication in many different tumor microenvironments.

     

A review of metabolism-associated biomarkers in lung cancer diagnosis and treatment

Introduction

Lung cancer continues to be the leading cause of cancer-related mortality worldwide. Early detection has proven essential to extend survival. Genomic and proteomic advances have provided impetus to the effort dedicated to detect and diagnose the disease at an earlier stage. Recently, the study of metabolites associated with tumor formation and progression has inaugurated the era of cancer metabolomics to aid in this effort.

Objectives

This review summarizes recent work regarding novel metabolites with the potential to serve as biomarkers for early lung tumor detection, evaluation of disease progression, and prediction of patient outcomes.

Method

We compare the metabolite profiling of cancer patients with that of healthy individuals, and the metabolites identified in tissue and biofluid samples and their usefulness as lung cancer biomarkers. We discuss metabolite alterations in tumor versus paired non-tumor lung tissues, as well as metabolite alterations in different stages of lung cancers and their usefulness as indicators of disease progression and overall survival. We evaluate metabolite dysregulation in different types of lung cancers, and those associated with lung cancer versus other lung diseases. We also examine metabolite differences between lung cancer patients and smokers/risk-factor individuals.

Result

Although an extensive list of metabolites has been evaluated to distinguish between these cases, refinement of methods is further required for adequate patient diagnosis and treatment.

Conclusion

We conclude that with technological advancement, metabolomics may be able to replace more invasive and costly diagnostic procedures while also providing the means to more effectively tailor treatment to patient-specific tumors.

     

Assessing the activity of nonsense-mediated mRNA decay in lung cancer

Background

Inhibition of nonsense-mediated mRNA decay (NMD) in tumor cells can suppress tumor growth through expressing new antigens whose mRNAs otherwise are degraded by NMD. Thus NMD inhibition is a promising approach for developing cancer therapies. Apparently, the success of this approach relies on the basal NMD activity in cancer cells. If NMD is already strongly inhibited in tumors, the approach would not work. Therefore, it is crucial to assess NMD activity in cancers to forecast the efficacy of NMD-inhibition based therapy.

Methods

Here we develop three metrics using RNA-seq data to measure NMD activity, and apply them to a dataset consisting of 72 lung cancer (adenocarcinoma) patients.

Results

We show that these metrics have good correlations, and that the NMD activities in adenocarcinoma samples vary among patients: some cancerous samples show significantly stronger NMD activities than the normal tissues while some others show the opposite pattern. The variation of NMD activities among these samples may be partly explained by the varying expression of NMD effectors.

Conclusions

In sum, NMD activity varies among lung cancerous samples, which forecasts varying efficacies of NMD-inhibition based therapy. The developed metrics can be further used in other cancer types to assess NMD activity.

     

Finding neoepitopes in mouse models of personalized cancer immunotherapy

Background

Cancer immunotherapy uses one’s own immune system to fight cancerous cells. As immune system is hard-wired to distinguish self and non-self, cancer immunotherapy is predicted to target cancerous cells specifically, therefore is less toxic than chemotherapy and radiation therapy, two major treatments for cancer. Cancer immunologists have spent decades to search for the specific targets in cancerous cells.

Methods

Due to the recent advances in high throughput sequencing and bioinformatics, evidence has merged that the neoantigens in cancerous cells are probably the cancer-specific targets that lead to the destruction of cancer.We will review the transplantable murine tumor models for cancer immunotherapy and the bioinformatics tools used to navigate mouse genome to identify tumor-rejecting neoantigens.

Results

Several groups have independently identified point mutations that can be recognized by T cells of host immune system. It is consistent with the note that the formation of peptide-MHC I-TCR complex is critical to activate T cells. Both anchor residue and TCR-facing residue mutations have been reported. While TCR-facing residue mutations may directly activate specific T cells, anchor residue mutations improve the binding of peptides to MHC I molecules, which increases the presentation of peptides and the T cell activation indirectly.

Conclusions

Our work indicates that the affinity of neoepitopes for MHC I is not a predictor for anti-tumor immune responses in mice. Instead differential agretopic index (DAI), the numerical difference of epitope-MHC I affinities between the mutated and un-mutated sequences is a significant predictor. A similar bioinformatics pipeline has been developed to generate personalized vaccines to treat human ovarian cancer in a Phase I clinical trial.

     

Evaluation of two different adjuvants with immunogenic uroplakin 3A-derived peptide for their ability to evoke an immune response in mice

Rationale

Organ- or tissue-specific antigens produced by normal tissue or by cancer cells could be used in cancer immunotherapy, to target the tumor. In our previous study, we induced T-cell-mediated, bladderspecific autoimmunity by targeting the bladder-specific protein Uroplakin 3A (UPK3A). UPK3A is a well-chosen target for developing an autoimmune response against bladder cancer since the antigen is also expressed in bladder tumors. To use this peptide, which was derived from the UPK3A protein in a bladder cancer vaccine study, it is necessary to induce a strong immune response. In this study, we aimed to develop a robust immune response in BALB/c mice using the well-characterized keyhole limpet hemocyanin (KLH)-conjugated peptide antigen (UPK3A 65-84) conjugated with an immunogenic carrier protein. In combination with the peptide, we used either Freund’s complete adjuvant (CFA) or CpG (cytosine-phosphate-guanine oligonucleotides) as effective adjuvants in order to overcome tumor tolerance.

Objectives

The immune response evoked by UPK3A 65-84 peptide, using two different adjuvants, was compared by detection of changes in the proliferative response of immune cells, in the cytokine profile, and in the immune cell populations.

Findings

We demonstrated that CpG, combined with KLH-UPK3A 65-84, promoted a more robust immune response, via induction of higher IL-2, IFN-γ, TNF-α, IL-17 production and activation of more immune cells (CD4⁺ T cells, CD8⁺ T cells, NK cells CD11b, CD45), than CFA and the KLHUPK3A 65-84.

Conclusion

CpG as an adjuvant combined with KLH-UPK3A 65-84 could be used in preclinical models of bladder cancer for the development of cancer immunotherapy strategies.

     

Monitoring cancer prognosis,diagnosis and treatment efficacy using metabolomics and lipidomics

Introduction

Cellular metabolism is altered during cancer initiation and progression, which allows cancer cells to increase anabolic synthesis, avoid apoptosis and adapt to low nutrient and oxygen availability. The metabolic nature of cancer enables patient cancer status to be monitored by metabolomics and lipidomics. Additionally, monitoring metabolic status of patients or biological models can be used to greater understand the action of anticancer therapeutics.

Objectives

Discuss how metabolomics and lipidomics can be used to (i) identify metabolic biomarkers of cancer and (ii) understand the mechanism-of-action of anticancer therapies. Discuss considerations that can maximize the clinical value of metabolic cancer biomarkers including case–control, prognostic and longitudinal study designs.

Methods

A literature search of the current relevant primary research was performed.

Results

Metabolomics and lipidomics can identify metabolic signatures that associate with cancer diagnosis, prognosis and disease progression. Discriminatory metabolites were most commonly linked to lipid or energy metabolism. Case–control studies outnumbered prognostic and longitudinal approaches. Prognostic studies were able to correlate metabolic features with future cancer risk, whereas longitudinal studies were most effective for studying cancer progression. Metabolomics and lipidomics can help to understand the mechanism-of-action of anticancer therapeutics and mechanisms of drug resistance.

Conclusion

Metabolomics and lipidomics can be used to identify biomarkers associated with cancer and to better understand anticancer therapies.